def test_decode(self):
funcdef = ExpandTreeRule(
NodeType("def", NodeConstraint.Node, False),
[("name", NodeType("value", NodeConstraint.Token, True)),
("body", NodeType("expr", NodeConstraint.Node, True))])
expr = ExpandTreeRule(
NodeType("expr", NodeConstraint.Node, False),
[("op", NodeType("value", NodeConstraint.Token, True)),
("arg0", NodeType("value", NodeConstraint.Token, True)),
("arg1", NodeType("value", NodeConstraint.Token, True))])
encoder = ActionSequenceEncoder(
Samples([funcdef, expr], [
NodeType("def", NodeConstraint.Node, False),
NodeType("value", NodeConstraint.Token, True),
NodeType("expr", NodeConstraint.Node, False)
], [("", "f")]), 0)
action_sequence = ActionSequence()
action_sequence.eval(ApplyRule(funcdef))
action_sequence.eval(GenerateToken("", "f"))
action_sequence.eval(GenerateToken("", "1"))
action_sequence.eval(ApplyRule(CloseVariadicFieldRule()))
expected_action_sequence = ActionSequence()
expected_action_sequence.eval(ApplyRule(funcdef))
expected_action_sequence.eval(GenerateToken("", "f"))
expected_action_sequence.eval(GenerateToken("", "1"))
expected_action_sequence.eval(ApplyRule(CloseVariadicFieldRule()))
result = encoder.decode(
encoder.encode_action(action_sequence,
[Token(None, "1", "1")])[:-1, 1:],
[Token(None, "1", "1")])
assert \
expected_action_sequence.action_sequence == result.action_sequence
def test_decode_invalid_tensor(self):
funcdef = ExpandTreeRule(
NodeType("def", NodeConstraint.Node, False),
[("name", NodeType("value", NodeConstraint.Token, False)),
("body", NodeType("expr", NodeConstraint.Node, True))])
expr = ExpandTreeRule(
NodeType("expr", NodeConstraint.Node, False),
[("op", NodeType("value", NodeConstraint.Token, False)),
("arg0", NodeType("value", NodeConstraint.Token, False)),
("arg1", NodeType("value", NodeConstraint.Token, False))])
encoder = ActionSequenceEncoder(
Samples([funcdef, expr], [
NodeType("def", NodeConstraint.Node, False),
NodeType("value", NodeConstraint.Token, False),
NodeType("expr", NodeConstraint.Node, False)
], [("", "f")]), 0)
assert encoder.decode(torch.LongTensor([[-1, -1, -1]]), []) is None
assert encoder.decode(torch.LongTensor([[-1, -1, 1]]), []) is None